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At a glance
Job overview
Sandbar is hiring a ML Engineer, Audio. Sandbar is an interface company in New York City that builds software, machine learning, and hardware products for partners such as Meta, CTRL‑labs, Google, Apple, Fitbit, Peloton, and Equinox. Their first product, Stream, is a private voice ring and conversational interface that will ship in Summer ’26. The role focuses on developing and deploying audio‑centric machine‑learning systems.
Key focus areas include Develop, evaluate, and deploy STT/TTS models spanning cloud to resource‑constrained on‑device settings, Optimize inference pipelines for latency, reliability, and concurrency, and Collaborate with ML/AI engineers, infrastructure engineers, designers, and cofounders on existing and future products.
Successful candidates bring 4+ Years Machine Learning Experience, Shipping ML-Based Products Experience, and Audio Voice Model Development Experience. Important skills include Machine Learning, Audio Modeling, Voice Modeling, Inference Optimization, Latency Optimization, and Reliability Engineering.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
About Sandbar
Sandbar is an interface company in New York City. We aim to augment individuals so we can each think, act, and move more freely. Our team has built SW, ML, and HW products across Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.
Our first product, Stream, is a self extension—a private voice ring and conversational interface. Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26.
Join us in creating technology that extends human thinking.
About
We’re looking for a machine learning engineer to help build Stream, a new conversational computer. As a machine learning engineer, you will develop a system which spans voice, memory, and agentic control. This role is perfect for someone cares deeply about real-world ML deployment and human-in-the-loop agentic interactions.
Responsibilities
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Develop, evaluate, and deploy STT/TTS models spanning cloud models to resource-constrained on-device settings
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Optimize inference pipelines for latency, reliability, and concurrency
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Work closely with other ML/AI engineers, infrastructure engineers, designers, and cofounders on existing and future products
Qualifications
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4+ years machine learning experience
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Experience developing audio / voice models is required
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Experience shipping ML-based products is required
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Passion for human-computer interaction
FTE Benefits
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Health, vision, and dental benefits
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Company-sponsored 401(k)
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Unlimited PTO and sick time
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Early stage equity
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